Modeling of Energy Management System for Fully Autonomous Vessels with Hybrid Renewable Energy Systems Using Nonlinear Model Predictive Control via Grey Wolf Optimization Algorithm by Harriet Laryea, Andrea Schiffauerova

“…The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. …”
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Information Diffusion Interpolation Model Based on the PSO-CV Algorithm and Its Application on Source Regions of the Yellow River by HUANG Huaping, YIN Kaixia, JIN Gaoyang

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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
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Multi-clause deduction algorithm based on dynamic combination optimization of strategies and its application(策略动态组合优化多元演绎算法及应用) by 郭海林(GUO Hailin), 曹锋(CAO Feng), 易见兵(YI Jianbing), 李俊(LI Jun), 吴贯锋(WU Guanfeng)

“…In order to better guide the clause selection in multi-clause deduction, multi-clause deduction method based on dynamic combination optimization of strategies is proposed. This method dynamically combines and iteratively optimizes the number of words and function term depth of clause, fully exploring the existing multi-clause deduction heuristic strategies while improving the adaptability of different problems to strategies, achieving efficient clause selection of multi-clause deduction. …”
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Synergistic Hierarchical Bi-Level Optimization of Demand Response Programs and Smart Inverter Volt/Var Control for Maximizing Hosting Capacity of Power Systems With Renewable-Based... by Zenhom M. Zenhom, Shady H. E. Abdel Aleem, Essam Aboul Zahab, Ziad M. Ali, Abdulaziz Almalaq, Tarek A. Boghdady

“…The pelican optimization algorithm (POA) is employed to solve the optimization problem and is compared with four other optimization techniques, demonstrating its good performance. …”
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Solving the 3D Multi-Objective Dynamic AUV Path Planning Problem Based on the Improved Morphin-Altruistic NSGAII Algorithm by Man Zhang, Jianhong Chen, Haibin Ouyang, Shangbin Long, Steven Li, Chunliang Zhang, Weiping Ding, Essam H. Houssein

“…Dynamic path planning seeks to find an optimal path for AUVs from a start point to the target while avoiding collisions with moving obstacles. …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…The result of Genetic Algorithm analysis also proved the model has converged to the optimal solution effectively, the best solution of X1 = 49.41, X2 = 110.62, X3 = 11.85 and X4 = 20 which gives the maximum removal efficiency = 94.64% of methylene blue. …”
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Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques by Saksham Anand, Venkatachalam Gopalan, Shenbaga Velu Pitchumani

“…Abstract This research focuses on enhancing the thermal conductivity of coir fibre-reinforced polyvinyl chloride (PVC) composites using advanced optimization techniques. While coir fibre adds sustainability and biodegradability, it poses challenges in achieving optimal thermal performance when integrated into PVC. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. …”
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Optimization of anti-MRSA compound production by Streptomyces sp. AR05 using an integrated RSM-ANN-GA approach by Fateh Merouane, Amani Kifadji, Racha Mansouri, Meroua Safa Mechouche, Chemes El-Houda Messaad, Anfal Bellebcir

“…Using the PlackettBurman design, the most important variables affecting the anti-MRSA activity were found to be peptone, CaCO3, and pH. These factors were optimized using Box-Behnken design, while RSM and ANN were utilized for modeling the experimental data. …”
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Estimation of Fresh and Hardened Properties of Self-Compacting Concrete by Optimized Radial Basis Function Methods by David Cadasse, Antonio Fontana

“…All in all, the RBFNN model developed by AOA outperforms others, with R2 values at 0.9607 (slump flow), 0.9651 (L-box), 0.9905 (V-funnel test), and 0.9934 (compressive strength), which depicts the capability of this algorithm for determining the optimal parameters of the RBFNN, While, it is worth mentioning than the model developed with GOA algorithm is also powerful.…”
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Optimal scheduling and energy management of a multi-energy microgrid with electric vehicles incorporating decision making approach and demand response by Genfu Xiao, Huan Liu, Javad Nabatalizadeh

“…One of the primary challenges in managing ME-MGs is reducing operational costs and emissions while addressing uncertainties. This study investigates the optimization and energy management (EM) in ME-MGs through the application of the Multi-Objective Walrus Optimization Algorithm (MOWaOA) combined with fuzzy decision-making techniques. …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

“…A neural network model is utilized to predict how the objective functions vary with six decision variables. The chosen optimization approach utilizes the genetic algorithm (GA) method. …”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment by A. Koraniany, G.R. Ansarifar

“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
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MPPT Efficiency in PV Arrays under Partial Shading Conditions:A Comparative Analysis of PSO and P&O Algorithms by Rachid Bennia, Cherif Larbes, Faiza Belhachat

“…This investigation presents a comparative analysis of two established algorithms: Particle Swarm Optimization (PSO) and Perturb and Observe (P&O), evaluating their respective capabilities in GMPP identification. …”
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Efficient Technique for Joint Parameter Estimation of Mixed Far Field Targets and Near Field Jammers in Phased Array Radar by Fawad Zaman, Sadiq Akbar, Zohaib Akhtar, Gridsada Phanomchoeng

“…A novel approach based on the Gradient Based Optimizer (GBO) algorithm and Marine Predators Algorithm (MPA) is proposed to estimate jointly the unknown parameters related to the far field targets and near field jammers. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…This article presents a symbiotic learning-based Grey Wolf Optimizer (SL-GWO) formulated through the introduction of symbiotic hunting and learning strategies to achieve a better trade-off between exploration and exploitation while standing immune to the curse of dimensionality. …”
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Improved ant colony algorithm based cloud computing user task scheduling algorithm by Sining LUO, Hualong WANG, Hongyu LI, Wei PENG

“…In recent years,with the development of power information,more and more power applications and tasks are deployed in the cloud.Because of the dynamic heterogeneity of cloud resources and power applications,it is a challenge in the cloud computing system to realize resource division and task scheduling.Power applications need to be able to achieve a rapid response and minimum completion time,and schedulers should consider the load of each cloud computing node to ensure the reliability of cloud computing.A task scheduling algorithm based on the algorithm of improving an ant colony was proposed to solve the problem of task scheduling in virtual machines.Through the improvement of the standard ant colony algorithm,the task scheduling time was reduced and load balancing was realized while minimizing the overall completion time.The results show that the algorithm can shorten the task scheduling time and realize the load balancing of cloud nodes,which provides technical basis for the optimization of power cloud computing.…”
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